[1] In this study, a geostatistically based estimator is developed that simultaneously includes all observed transient hydrographs from hydraulic tomography to map aquifer heterogeneity. To analyze tomography data, a data preprocessing procedure (including diagnosing and wavelet denoising analysis) is recommended. A least squares approach is then introduced to estimate effective parameters and spatial statistics of heterogeneity that are the required inputs for the geostatistical estimator. Since wavelet denoising does not completely remove noise from observed hydrographs, a stopping criterion is established to avoid overexploitation of the imperfect hydrographs. The estimator and the procedures are then tested in a synthetic, cross-sectional aquifer with hierarchical heterogeneity and a vertical sandbox with prearranged heterogeneity. Results of the test indicate that with this estimator and preprocessing procedures, hydraulic tomography can effectively map hierarchical heterogeneity in the synthetic aquifer as well as in the sandbox. In addition, the study shows that using the estimated hydraulic conductivity and specific storage fields of the sandbox, the classic groundwater flow model accurately predicts temporal and spatial distributions of drawdown induced by an independent pumping event in the sandbox. On the other hand, the classic groundwater flow model yields less satisfactory results when equivalent homogeneous properties of the sandbox are used.

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Abstract:An increasing impervious area is quickly extending over the Wu-Tu watershed due to the endless demands of the people. Generally, impervious paving is a major result of urbanization and more recently has had the potential to produce more enormous flood disasters than those of the past. In this study, 40 available rainfall-runoff events were chosen to calibrate the applicable parameters of the models and to determine the relationships between the impervious surfaces and the calibrated parameters. Model inputs came from the outcomes of the block kriging method and the non-linear programming method. In the optimal process, the shuffled complex evolution method and three criteria were applied to compare the observed and simulated hydrographs. The tendencies of the variations of the parameters with their corresponding imperviousness were established through regression analysis. Ten cases were used to examine the established equations of the parameters and impervious covers. Finally, the design flood routines of various return periods were furnished through use of approaches containing a design storm, block kriging, the SCS model, and a rainfall-runoff model with established functional relationships. These simulated flood hydrographs were used to compare and understand the past, present, and future hydrological conditions of the watershed studied. In the research results, the time to peak of flood hydrographs for various storms was diminished approximately from 11 h to 6 h in different decrements, whereas peak flow increased respectively from 127 m 3 s 1 to 629 m 3 s 1 for different storm intensities. In addition, this study provides a design diagram for the peak flow ratio to help engineers and designers to construct hydraulic structures efficiently and prevent possible damage to human life and property.

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While hydraulic tomography (HT) is a mature aquifer characterization technology, its applications to characterize hydrogeology of kilometer-scale fault and fracture zones are rare. This paper sequentially analyzes datasets from two new pumping tests as well as those from two previous pumping tests analyzed by Illman et al. (2009) at a fractured granite site in Mizunami, Japan. Results of this analysis show that datasets from two previous pumping tests at one side of a fault zone as used in the previous study led to inaccurate mapping of fracture and fault zones. Inclusion of the datasets from the two new pumping tests (one of which was conducted on the other side of the fault) yields locations of the fault zone consistent with those based on geological mapping. The new datasets also produce a detailed image of the irregular fault zone, which is not available from geological investigation alone and the previous study. As a result, we conclude that if prior knowledge about geological structures at a field site is considered during the design of HT surveys, valuable non-redundant datasets about the fracture and fault zones can be collected. Only with these non-redundant data sets, can HT then be a viable and robust tool for delineating fracture and fault distributions over kilometer scales, even when only a limited number of boreholes are available. In essence, this paper proves that HT is a new tool for geologists, geophysicists, and engineers for mapping large-scale fracture and fault zone distributions.

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[1] Data from tomographic surveys make an inverse problem better posed in comparison to the data from a single excitation source. A tomographic survey provides different coverages and perspectives of subsurface heterogeneity: nonfully redundant information of the subsurface. Fusion of these pieces of information expands and enhances the capability of a conventional survey, provides cross validation of inverse solutions, and constrains inherently ill posed field-scale inverse problems. Basin-scale tomography requires energy sources of great strengths. Spatially and temporally varying natural stimuli are ideal energy sources for this purpose. In this study, we explore the possibility of using river stage variations for basin-scale subsurface tomographic surveys. Specifically, we use numerical models to simulate groundwater level changes in response to temporal and spatial variations of the river stage in a hypothetical groundwater basin. We then exploit the relation between temporal and spatial variations of well hydrographs and river stage to image subsurface heterogeneity of the basin. Results of the numerical exercises are encouraging and provide insights into the proposed river stage tomography. Using naturally recurrent stimuli such as river stage variations for characterizing groundwater basins could be the future of geohydrology. However, it calls for implementation of sensor networks that provide long-term and spatially distributed monitoring of excitation as well as response signals on the land surface and in the subsurface.